How to ID a bee

The algorithm quickly identifies a bee’s species based on the patterns in its wings, cross-referencing unknown bee wings with research images like this one.

It’s a vanishing act that has puzzled everyone from top entomologists to characters on the popular British sci-fi series Doctor Who. What’s happening to the honeybees? Every year, colony collapse disorder decimates the European honeybee population in the United States—and the disappearance of these key pollinators has serious implications for growers who depend on honeybees to pollinate their crops.

In Wisconsin, European honeybees are only one of about 600 different bee species. And the important question many not be where the missing bees are— but rather, which bees are still here, and what are they doing, says UW-Madison entomologist Claudio Gratton. “What we want to know is how this diversity of bees is affecting pollination in Wisconsin crops,” he says.

But the big bottleneck in that endeavor starts with the people who can ID bees: There are fewer than a half-dozen people in North America who have the expertise to classify multitudes of bee specimens, and the turnaround time for a submitted sample can be as long as a year.

Gratton thought that there had to be a more efficient way to do things, so he contacted Electrical and Computer Engineering Professor Bill Sethares to ask if he could create a system for digital taxonomy, possibly even an iPhone application, that could quickly and accurately identify bee species from images of their intricately veined wings. “Bees have wings that look like a series of membranes arranged in a pattern,” says Sethares.

He and his graduate students Chris Hall, Mark Lenz and Chuck Hatt developed an algorithm that can learn to recognize those patterns and identify a bee species based on a database of images from Gratton’s research lab. To increase both the number of images and the diversity of species that could be identified, graduate student Mark Lenz is building a website, idBee, through which users can contribute to their own photos of bee wings—thus providing a larger pool of photos for testing the algorithm. He hopes to fully launch the website in 2012.

With some improvements to the image-processing and learning algorithms, Lenz also is optimistic the iPhone app will become a reality. “At that point, if a smartphone has a camera of high enough quality, we should be able to create an app for schoolchildren,” he says. Gratton and his team are willing to be patient because the potential of an easy-to-use app could pay enormous dividends—both for research purposes and as a way involve the public in what they do.

“How many eyes can you get looking for things for you? You end up seeing a lot of things that a professional entomologist might not see—because we just can’t be everywhere,” Gratton says.